dsfx/docs/requirements/nfr-3-scalability-and-capacity.md

NFR-3: Scalability & Capacity

1. Overview

This document defines the requirements for ensuring that the system can scale efficiently as usage, file sizes, user numbers, and node counts grow. The goal is to ensure that the system’s performance and resource utilization remain within acceptable limits even when handling increased loads and when deployed across many nodes. Scalability and capacity planning are essential to guarantee consistent performance under high volume and stress conditions.

2. Objectives & Scope

2.1 Objectives

• Linear or Near-Linear Scaling: The system should scale its processing, storage, and communication capabilities in proportion to growth in users, file operations, and nodes.

• Efficient Resource Utilization: Optimize CPU, memory, disk I/O, and network bandwidth to accommodate expanding workloads without degradation.

• High Throughput Maintenance: Ensure that increases in data volume or node count do not cause bottlenecks in file processing, replication, or synchronization.

2.2 Scope

• Applies to backend processing (encryption, partitioning, replication), data storage management, and inter-node communications.
• Covers performance under normal growth conditions as well as stress scenarios simulated via deterministic testing.
• Encompasses both vertical scaling (improving performance on a single node) and horizontal scaling (adding more nodes).

3. Detailed Requirements

3.1 System Performance Under Load

• Throughput Benchmarks:

  • Define target throughput with respect to number of file operations per minute/hour.
  • Establish benchmarks for performance as nodes or user counts increase.

• Resource Efficiency:

  • Implement mechanisms for dynamic load balancing and resource allocation to prevent any single node from being overwhelmed.
  • Support distributed storage paradigms (such as content-addressable storage) to minimize duplication and resource waste.

3.2 Elastic Scaling Strategies

• Horizontal Scalability:

  • Enable the addition of nodes to increase processing power and storage capacity with minimal reconfiguration.
  • Integrate with orchestration tools (e.g., Kubernetes) to facilitate automatic scaling based on load.

• Vertical Scalability:

  • Allow nodes to use hardware acceleration and optimized resources to improve performance on larger workloads.

3.3 Bottleneck Identification and Mitigation

• Profiling and Stress Testing:
  • Establish periodic testing procedures under simulated high-load conditions to identify performance bottlenecks (e.g., CPU, memory, network).
  • Implement caching strategies, asynchronous processes, and efficient algorithms to mitigate identified bottlenecks.

4. Measurable Criteria & Test Cases

4.1 Load Testing

• Simulate increased numbers of concurrent file uploads, downloads, and replication operations across many nodes.
• Measure throughput, latency, and resource usage as the load increases.
• Validate that performance metrics remain within pre-defined acceptable thresholds.

4.2 Scalability Benchmarks

• Establish baseline performance with a known number of nodes and users.
• Incrementally increase load and record the scaling behavior; ideally, performance degradation should be minimal or linear.
• Use horizontal scaling tests to add nodes dynamically and verify that overall throughput increases proportionately.

4.3 Capacity Planning Tests

• Simulate scenarios with large file sizes and high data volumes.
• Monitor system behavior (e.g., disk I/O, network bandwidth usage) to ensure that capacity limits are not exceeded.
• Validate that distributed storage mechanisms efficiently leverage available resources.

5. Dependencies & Integration Points

• Monitoring and Logging Tools:
  • Integration with system monitors to continuously track performance metrics and resource utilization.
• Orchestration Platforms:
  • Compatibility with container orchestration tools to facilitate horizontal scaling.
• Deterministic Simulation Framework:
  • Use simulation to reproduce high-load scenarios reliably.

6. Conclusion

NFR-3 ensures that the system can scale as demand grows, maintaining high performance and efficient resource utilization. By establishing clear throughput benchmarks, elastic scaling strategies, and regular stress testing, the system will remain robust and responsive even under significant load and capacity stress.